Applied Linear Statistical Models
About: This article is published in Journal of the American Statistical Association.The article was published on 1986-12-01. It has received 10217 citations till now. The article focuses on the topics: Statistical model.
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TL;DR: A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD.
Abstract: Background—The objective of this study was to examine the association of Joint National Committee (JNC-V) blood pressure and National Cholesterol Education Program (NCEP) cholesterol categories with coronary heart disease (CHD) risk, to incorporate them into coronary prediction algorithms, and to compare the discrimination properties of this approach with other noncategorical prediction functions. Methods and Results—This work was designed as a prospective, single-center study in the setting of a community-based cohort. The patients were 2489 men and 2856 women 30 to 74 years old at baseline with 12 years of follow-up. During the 12 years of follow-up, a total of 383 men and 227 women developed CHD, which was significantly associated with categories of blood pressure, total cholesterol, LDL cholesterol, and HDL cholesterol (all P,.001). Sex-specific prediction equations were formulated to predict CHD risk according to age, diabetes, smoking, JNC-V blood pressure categories, and NCEP total cholesterol and LDL cholesterol categories. The accuracy of this categorical approach was found to be comparable to CHD prediction when the continuous variables themselves were used. After adjustment for other factors, ’28% of CHD events in men and 29% in women were attributable to blood pressure levels that exceeded high normal ($130/85). The corresponding multivariable-adjusted attributable risk percent associated with elevated total cholesterol ($200 mg/dL) was 27% in men and 34% in women. Conclusions—Recommended guidelines of blood pressure, total cholesterol, and LDL cholesterol effectively predict CHD risk in a middle-aged white population sample. A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD. (Circulation. 1998;97:1837-1847.)
9,227 citations
TL;DR: The wrapper method searches for an optimal feature subset tailored to a particular algorithm and a domain and compares the wrapper approach to induction without feature subset selection and to Relief, a filter approach tofeature subset selection.
8,610 citations
TL;DR: In this article, a correlational study examined relationships between motivational orientation, self-regulated learning, and classroom academic performance for 173 seventh graders from eight science and seven English classes.
Abstract: A correlational study examined relationships between motivational orientation, self-regulated learning, and classroom academic performance for 173 seventh graders from eight science and seven English classes. A self-report measure of student self-efficacy, intrinsic value, test anxiety, self-regulation, and use of learning strategies was administered, and performance data were obtained from work on classroom assignments. Self-efficacy and intrinsic value were positively related to cognitive engagement and performance. Regression analyses revealed that, depending on the outcome measure, self-regulation, self-efficacy, and test anxiety emerged as the best predictors of performance. Intrinsic value did not have a direct influence on performance but was strongly related to self-regulation and cognitive strategy use, regardless of prior achievement level. The implications of individual differences in motivational orientation for cognitive engagement and self-regulation in the classroom are discussed. Self-regulation of cognition and behavior is an important aspect of student learning and academic performance in the classroom context (Corno & Mandinach, 1983; Corno & Rohrkemper, 1985). There are a variety of definitions of selfregulated learning, but three components seem especially important for classroom performance. First, self-regulated learning includes students' metacognitive strategies for planning, monitoring, and modifying their cognition (e.g., Brown, Bransford, Campione, & Ferrara, 1983; Corno, 1986; Zim
7,442 citations
TL;DR: A meta-analysis of the transformational leadership literature using the Multifactor Leadership Questionnaire (MLQ) was conducted to compute an average effect for different leadership scales, and probe for certain moderators of the leadership style-effectiveness relationship as mentioned in this paper.
Abstract: A meta-analysis of the transformational leadership literature using the Multifactor Leadership Questionnaire (MLQ) was conducted to (a) integrate the diverse findings, (b) compute an average effect for different leadership scales, and (c) probe for certain moderators of the leadership style-effectiveness relationship. Transformational leadership scales of the MLQ were found to be reliable and significantly predicted work unit effectiveness across the set of studies examined. Moderator variables suggested by the literature, including level of the leader (high or low), organizational setting (public or private), and operationalization of the criterion measure (subordinate perceptions or organizational measures of effectiveness), were empirically tested and found to have differential impacts on correlations between leader style and effectiveness. The operationalization of the criterion variable emerged as a powerful moderator. Unanticipated findings for type of organization and level of the leader are explored regarding the frequency of transformational leader behavior and relationships with effectiveness.
2,836 citations
TL;DR: Analysis of the human event-related brain potentials (ERPs) accompanying errors provides evidence for a neural process whose activity is specifically associated with monitoring and compensating for erroneous behavior.
Abstract: Humans can monitor actions and compensate for errors. Analysis of the human event-related brain potentials (ERPs) accompanying errors provides evidence for a neural process whose activity is specifically associated with monitoring and compensating for erroneous behavior. This error-related activity is enhanced when subjects strive for accurate performance but is diminished when response speed is emphasized at the expense of accuracy. The activity is also related to attempts to compensate for the erroneous behavior.
2,732 citations